A crystal-clear business view into predictive AI projects – Gooder AI hands-on #5
This is the 5th of several short how-to, hands-on videos that will get you started using Gooder AI to *valuate* and supercharge your predictive AI projects.
If you're not already familiar with the purpose of Gooder AI and what it means to plan machine learning model deployment by viewing the potential business value, start with this video: https://youtu.be/6seERbo0-vE
See also this demo of the Gooder AI chatbot: https://youtu.be/FP27JpdQsjI
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Access Gooder AI hands-on: https://www.gooder.ai/handson
After this, watch the next how-to video: https://youtu.be/J5ya8UTMvW8
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PROFIT NOT AUC! How to make the much-needed shift for predictive AI (enterprise machine learning) from technical metrics to business metrics.
Data scientists always *evaluate* their AI models – but almost never *valuate* them. To pursue business value, stakeholders must visualize a model's business performance. Gooder AI does just that.
https://www.gooder.ai/
There’s a fundamental problem with the typical model development process: It evaluates models in terms of technical metrics like AUC/precision/recall without also including business metrics like profit and savings – the stuff that actually matters to the business.
This is a serious problem – if you're not measuring business value, you’re not pursuing business value. Further, those technical metrics fail to provide your client/stakeholder meaningful visibility – she doesn’t care about AUC. How is she supposed to authorize deployment?
That’s why Machine Learning Week founder and former Columbia professor Eric Siegel co-founded Gooder AI. It addresses this fundamental issue by way of its SaaS product, the first full-scale platform for machine learning valuation – to maximize the value of models by testing and visualizing their business performance.
Spoiler alert: Unlike technical measures, a model’s business performance (profit, savings, etc.) depends on how you use it. So assessing the business value requires a specialized visualization solution, one that allows you to interactively try out what-if deployment scenarios. This includes setting various business parameters, which are subject to change, and positioning the decision boundary to estimate the potential deployed value.
Watch Eric demo Gooder AI and show how you can use it to drive ML deployment to maximize business impact.
https://www.gooder.ai/
Patent pending, Gooder AI, Inc.
This is the 5th of several short how-to, hands-on videos that will get you started using Gooder AI to *valuate* and supercharge your predictive AI projects.
If you’re not already familiar with the purpose of Gooder AI and what it means to plan machine learning model deployment by viewing the potential business value, start with this video: https://youtu.be/6seERbo0-vE
See also this demo of the Gooder AI chatbot: https://youtu.be/FP27JpdQsjI
———————–
Access Gooder AI hands-on: https://www.gooder.ai/handson
After this, watch the next how-to video: https://youtu.be/J5ya8UTMvW8
———————–
PROFIT NOT AUC! How to make the much-needed shift for predictive AI (enterprise machine learning) from technical metrics to business metrics.
Data scientists always *evaluate* their AI models – but almost never *valuate* them. To pursue business value, stakeholders must visualize a model’s business performance. Gooder AI does just that.
https://www.gooder.ai/
There’s a fundamental problem with the typical model development process: It evaluates models in terms of technical metrics like AUC/precision/recall without also including business metrics like profit and savings – the stuff that actually matters to the business.
This is a serious problem – if you’re not measuring business value, you’re not pursuing business value. Further, those technical metrics fail to provide your client/stakeholder meaningful visibility – she doesn’t care about AUC. How is she supposed to authorize deployment?
That’s why Machine Learning Week founder and former Columbia professor Eric Siegel co-founded Gooder AI. It addresses this fundamental issue by way of its SaaS product, the first full-scale platform for machine learning valuation – to maximize the value of models by testing and visualizing their business performance.
Spoiler alert: Unlike technical measures, a model’s business performance (profit, savings, etc.) depends on how you use it. So assessing the business value requires a specialized visualization solution, one that allows you to interactively try out what-if deployment scenarios. This includes setting various business parameters, which are subject to change, and positioning the decision boundary to estimate the potential deployed value.
Watch Eric demo Gooder AI and show how you can use it to drive ML deployment to maximize business impact.
https://www.gooder.ai/
Patent pending, Gooder AI, Inc.
